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SUMMARY:Predicting antibiotic resistance evolution - Fernanda Pinheiro\, H
 uman Technopole\, Milan\, Italy.
DTSTART:20241121T140000Z
DTEND:20241121T150000Z
UID:TALK224764@talks.cam.ac.uk
CONTACT:Fulvio Forni
DESCRIPTION:In this talk\, I will present a fitness model that predicts gr
 owth rates of common resistance mutants from their effects on cell metabol
 ism. The model maps metabolic effects of resistance mutations in drug-free
  environments and under drug challenge\; the resulting fitness trade-off d
 efines a Pareto surface of resistance evolution. It predicts evolutionary 
 trajectories of growth rates and resistance levels\, which characterize Pa
 reto resistance mutations emerging at different drug dosages. The model al
 so predicts the prevalent resistance mechanism depending on drug and nutri
 ent levels: low-dosage drug defence is mounted by regulation\, evolution o
 f distinct metabolic sectors sets in at successive threshold dosages. Evol
 utionary resistance mechanisms include membrane permeability changes and d
 rug target mutations. These predictions are confirmed by empirical growth 
 inhibition curves and genomic data of Escherichia coli populations. In a b
 roader context\, I will discuss how systems biology can serve as a powerfu
 l tool for ecological and evolutionary predictions.\n\nThe seminar will be
  held in the LR3A \, Department of Engineering\, and online (zoom): https:
 //newnham.zoom.us/j/92544958528?pwd=YS9PcGRnbXBOcStBdStNb3E0SHN1UT09
LOCATION:LR3A\, Department of Engineering and online (Zoom)
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